Dynamic batching policies for an on-demand video server
Multimedia Systems
On optimal piggyback merging policies for video-on-demand systems
Proceedings of the 1996 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Metropolitan area video-on-demand service using pyramid broadcasting
Multimedia Systems
Online computation and competitive analysis
Online computation and competitive analysis
Patching: a multicast technique for true video-on-demand services
MULTIMEDIA '98 Proceedings of the sixth ACM international conference on Multimedia
Improving bandwidth efficiency of video-on-demand servers
IC3N '97 Selected papers of the 6th international conference on Computer communications and networks
Optimal and efficient merging schedules for video-on-demand servers
MULTIMEDIA '99 Proceedings of the seventh ACM international conference on Multimedia (Part 1)
Competitive on-line stream merging algorithms for media-on-demand
SODA '01 Proceedings of the twelfth annual ACM-SIAM symposium on Discrete algorithms
The dyadic stream merging algorithm
Journal of Algorithms
Minimizing Bandwidth Requirements for On-Demand Data Delivery
IEEE Transactions on Knowledge and Data Engineering
On Optimal Batching Policies for Video-on-Demand Storage Servers
ICMCS '96 Proceedings of the 1996 International Conference on Multimedia Computing and Systems
Competitive Analysis of On-line Stream Merging Algorithms
MFCS '02 Proceedings of the 27th International Symposium on Mathematical Foundations of Computer Science
On-line stream merging, max span, and min coverage
CIAC'03 Proceedings of the 5th Italian conference on Algorithms and complexity
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This paper is concerned with on-line scheduling algorithms for merging streams in a video-on-demand system so as to minimize the server bandwidth. We present the first algorithm that has a constant competitive factor (precisely, 5). Our algorithm, unlike previous ones, is not limited to the scenario where clients are equipped with large buffer and client receiving bandwidth. It remains 5-competitive in all settings of buffer size and receiving bandwidth. Technically speaking, our algorithm is based on a novel observation that the behavior of any schedule can be modeled by a rectilinear (binary) tree on a grid. This observation eases the analysis of our algorithm as well as the optimal algorithm.